serverless-plugin-datadog

What is serverless-plugin-datadog?

The serverless-plugin-datadog npm package is designed to integrate Datadog monitoring and observability features into Serverless Framework applications. It allows you to automatically instrument your AWS Lambda functions with Datadog, enabling you to monitor performance, track metrics, and set up alerts.

What are serverless-plugin-datadog's main functionalities?

Automatic Instrumentation

This feature automatically instruments your AWS Lambda functions with Datadog. By adding the plugin to your Serverless Framework configuration and setting the appropriate custom options, you can enable Datadog layers, flush metrics to logs, and set the log level.

{
  "plugins": ["serverless-plugin-datadog"],
  "custom": {
    "datadog": {
      "addLayers": true,
      "flushMetricsToLogs": true,
      "logLevel": "info"
    }
  }
}

Custom Metrics

This feature allows you to enable custom metrics for your Lambda functions. By setting the `customMetrics` option to true, you can send custom metrics from your Lambda functions to Datadog.

{
  "custom": {
    "datadog": {
      "customMetrics": true
    }
  }
}

Tracing

This feature enables tracing for your Lambda functions. By setting `enableXrayTracing` and `enableDDTracing` to true, you can enable AWS X-Ray and Datadog tracing, respectively, to get detailed insights into your function's performance.

{
  "custom": {
    "datadog": {
      "enableXrayTracing": true,
      "enableDDTracing": true
    }
  }
}

Other packages similar to serverless-plugin-datadog

serverless-plugin-splunk

The serverless-plugin-splunk package integrates Splunk logging and monitoring with Serverless Framework applications. It provides similar functionalities to serverless-plugin-datadog, such as automatic instrumentation and custom metrics, but it is tailored for Splunk's monitoring and observability tools.

serverless-plugin-aws-alerts

The serverless-plugin-aws-alerts package allows you to set up AWS CloudWatch alerts for your Serverless Framework applications. While it does not provide the same level of integration with a third-party monitoring service like Datadog, it offers a way to monitor and alert on AWS Lambda function performance using AWS-native tools.

README

---

title: Datadog Serverless Plugin kind: documentation aliases:

• /serverless/serverless_integrations/plugin/ dependencies: ["https://github.com/DataDog/serverless-plugin-datadog/blob/master/README.md"]

---

Datadog recommends the Serverless Framework Plugin for developers using the Serverless Framework to deploy their serverless applications. The plugin automatically enables instrumentation for applications to collect metrics, traces, and logs by:

• Installing the Datadog Lambda library to your Lambda functions as a Lambda layer.
• Installing the Datadog Lambda Extension to your Lambda functions as a Lambda layer (addExtension) or subscribing the Datadog Forwarder to your Lambda functions' log groups (forwarderArn).
• Making the required configuration changes, such as adding environment variables or additional tracing layers, to your Lambda functions.

Getting started

To quickly get started, follow the installation instructions for Python, Node.js, Ruby, Java, Go, or .NET and view your function's enhanced metrics, traces, and logs in Datadog. These instructions will get you a basic working setup. If working in Ruby or Go, further code changes are required.

Upgrade

Each version of the plugin is published with a specific set of versions of the Datadog Lambda layers. To pick up new features and bug fixes provided by the latest versions of Datadog Lambda layers, upgrade the serverless framework plugin. Test the new version before applying it on your production applications.

More configuration options

To further configure your plugin, use the following custom parameters in your serverless.yml:

Parameter	Description
flushMetricsToLogs	Send custom metrics by using logs with the Datadog Forwarder Lambda function (recommended). Defaults to true. To use an encrypted key, set apiKMSKey or apiKeySecretArn in the configuration. flushMetricsToLogs is ignored when addExtension is true.
site	Set which Datadog site to send data to. This is only used when flushMetricsToLogs is false or addExtension is true. Possible values are datadoghq.com, datadoghq.eu, us3.datadoghq.com, us5.datadoghq.com, and ddog-gov.com. The default is datadoghq.com.
apiKey	Datadog API key. Required when flushMetricsToLogs is false or addExtension is true. Defining apiKey adds the Datadog API key directly to your Lambda functions as an environment variable. For more information about getting a Datadog API key, see the API key documentation. Can also be set through the DATADOG_API_KEY environment variable.
appKey	Datadog app key. Only needed when the monitors field is defined. Can also be set through the DATADOG_APP_KEY environment variable.
apiKeySecretArn	An alternative to using the apiKey field. The ARN of the secret storing the Datadog API key in AWS Secrets Manager. Use this parameter if you're storing your secrets in AWS Secrets Manager, and when flushMetricsToLogs is false or addExtension is true. If set, remember to add the secretsmanager:GetSecretValue permission to the Lambda execution role.
apiKMSKey	An alternative to using the apiKey field. Datadog API key encrypted using KMS. Use this parameter if you're storing your secrets with KMS, and if flushMetricsToLogs is false or addExtension is true. Defining apiKMSKey adds the Datadog API Key directly to your Lambda functions as an environment variable.
captureLambdaPayload	(Experimental) This optional setting configures Datadog ingestion for incoming and outgoing AWS Lambda payloads. Function request and response values are added as part of outgoing APM spans sent to Datadog, and require Datadog APM to be configured on your function. You can obfuscate fields in the Lambda payload by using the replace_tags block within apm_config settings in datadog.yaml. Defaults to false.
addLayers	Whether to install the Datadog Lambda library as a layer. Defaults to true. Set to false when you plan to package the Datadog Lambda library to your function's deployment package on your own so that you can install a specific version of the Datadog Lambda library (Python or Node.js).
addExtension	Whether to install the Datadog Lambda Extension as a layer. Defaults to true. When enabled, it's required to set the environment variable DATADOG_API_KEY, or the configuration values apiKMSKey or apiKeySecretArn. Learn more about the Datadog Lambda Extension Layer in the documentation. Note: AWS only supports Lambda Extensions for certain runtimes.
logLevel	The log level, set to DEBUG for extended logging.
enableXrayTracing	Set true to enable X-Ray tracing on the Lambda functions and API Gateway integrations. Defaults to false.
enableDDTracing	Enable Datadog tracing on the Lambda function. Note: This applies only to integrations using the Datadog Extension. Defaults to true.
enableDDLogs	Enable Datadog log collection for the Lambda function. Note: This setting has no effect on logs sent by the Datadog Forwarder. Defaults to true.
enableSourceCodeIntegration	Enable Datadog source code integration for the function. This feature links your Github repository information to the function in Datadog and allows you to view stack traces from Datadog directly in Github. For more information, see Source Code Integration.
subscribeToApiGatewayLogs	Enable automatic subscription of the Datadog Forwarder to API Gateway log groups. Defaults to true.
subscribeToHttpApiLogs	Enable automatic subscription of the Datadog Forwarder to HTTP API log groups. Defaults to true.
subscribeToWebsocketLogs	Enable automatic subscription of the Datadog Forwarder to WebSocket log groups. Defaults to true.
forwarderArn	Setting this parameter subscribes the given Datadog forwarder to the Lambda functions’ CloudWatch log groups. Required when enableDDTracing is set to true unless the subscription is otherwise applied. For example, if a Datadog Forwarder subscription is applied using Datadog's AWS Integration, then forwarderArn is not required.
integrationTesting	Set true when running integration tests. This bypasses the validation of the Forwarder ARN and the addition of Datadog Monitor output links. Defaults to false.
enableTags	When set, automatically tag the Lambda functions with the service and env tags using the service and stage values from the serverless application definition. It does NOT override if a service or env tag already exists. Defaults to true.
injectLogContext	When set, the Lambda layer automatically patches console.log with Datadog's tracing IDs. Defaults to true.
exclude	When set, this plugin ignores all specified functions. Use this parameter if you have any functions that should not include Datadog functionality. Defaults to [].
enabled	When set to false, the Datadog plugin stays inactive. Defaults to true. You can control this option using an environment variable. For example, use enabled: ${strToBool(${env:DD_PLUGIN_ENABLED, true})} to activate/deactivate the plugin during deployment. Alternatively, you can also use the value passed in through --stage to control this option—see example.
monitors	When defined, the Datadog plugin will configure monitors for the deployed function. Requires setting DATADOG_API_KEY and DATADOG_APP_KEY in your environment. To learn how to define monitors, see To Enable and Configure a Recommended Serverless Monitor.
customHandler	When set, the specified handler is set as the handler for all the functions. By default, the handler is set to /opt/nodejs/node_modules/datadog-lambda-js/handler.handler if addLayers is set to true, or node_modules/datadog-lambda-js/dist/handler.handler if addLayers is set to false.
failOnError	When set, this plugin will throw an error if any custom Datadog monitors fail to create or update. This occurs after deploy, but will cause the result of serverless deploy to return a nonzero exit code (to fail user CI). Defaults to false.

To use any of these parameters, add a custom > datadog section to your serverless.yml similar to this example:

custom:
  datadog:
    flushMetricsToLogs: true
    apiKeySecretArn: "{Datadog_API_Key_Secret_ARN}"
    apiKMSKey: "{Encrypted_Datadog_API_Key}"
    addLayers: true
    logLevel: "info"
    enableXrayTracing: false
    enableDDTracing: true
    enableDDLogs: true
    subscribeToAccessLogs: true
    forwarderArn: arn:aws:lambda:us-east-1:000000000000:function:datadog-forwarder
    enableTags: true
    injectLogContext: true
    exclude:
      - dd-excluded-function

Note: If you use webpack, Datadog recommends using the prebuilt layers by setting addLayers to true, which is the default, and add datadog-lambda-js and dd-trace to the externals section of your webpack config.

Note: Many of the above configuration values require setting DATADOG_API_KEY in your environment. If you store these values in AWS Secrets Manager or AWS KMS, refer to the above options apiKeySecretArn and apiKMSKey to pull your Datadog API key from the correct location.

TypeScript

If you are using serverless-typescript, make sure that serverless-datadog is above the serverless-typescript entry in your serverless.yml. The plugin will automatically detect .ts files.

plugins:
  - serverless-plugin-datadog
  - serverless-typescript

If you use TypeScript, you may encounter the error of missing type definitions. A missing type definition happens when you use the prebuilt layers (for example, set addLayers to true, which is the default) and need to import helper functions from the datadog-lambda-js and dd-trace packages to submit custom metrics or instrument a specific function. To resolve the error, add datadog-lambda-js and dd-trace to the devDependencies list of your project's package.json.

Webpack

dd-trace is known to be not compatible with webpack due to the use of conditional import and other issues. If using webpack, make sure to mark datadog-lambda-js and dd-trace as externals for webpack, so webpack knows these dependencies will be available in the runtime. You should also remove datadog-lambda-js and dd-trace from package.json and the build process to ensure you're using the versions provided by the Datadog Lambda Layer.

serverless-webpack

If using serverless-webpack, make sure to also exclude datadog-lambda-js and dd-trace in your serverless.yml in addition to declaring them as external in your webpack config file.

webpack.config.js

var nodeExternals = require("webpack-node-externals");

module.exports = {
  // we use webpack-node-externals to excludes all node deps.
  // You can manually set the externals too.
  externals: [nodeExternals(), "dd-trace", "datadog-lambda-js"],
};

serverless.yml

custom:
  webpack:
    includeModules:
      forceExclude:
        - dd-trace
        - datadog-lambda-js

Forwarder

The Datadog Forwarder Lambda function needs to be installed and subscribed to your Lambda functions' log groups. The plugin automatically creates the log subscriptions when the Forwarder's ARN is supplied via the forwarderArn option.

If you run into the following error, double check the supplied Forwarder ARN is correct and ensure it is from the same region and account where your serverless application is deployed.

An error occurred: GetaccountapiLogGroupSubscription - Could not execute the lambda function. Make sure you have given CloudWatch Logs permission to execute your function. (Service: AWSLogs; Status Code: 400; Error Code: InvalidParameterException).

Disable Plugin for Particular Environment

If you'd like to turn off the plugin based on the environment (passed via --stage), you can use something similar to the example below.

provider:
  stage: ${self:opt.stage, 'dev'}

custom:
  staged: ${self:custom.stageVars.${self:provider.stage}, {}}

  stageVars:
    dev:
      dd_enabled: false

  datadog:
    enabled: ${self:custom.staged.dd_enabled, true}

Serverless Monitors

There are seven recommended monitors with default values pre-configured.

Monitor	Metrics	Threshold	Serverless Monitor ID
High Error Rate	aws.lambda.errors/aws.lambda.invocations	>= 10%	high_error_rate
Timeout	aws.lambda.duration.max/aws.lambda.timeout	>= 1	timeout
Out of Memory	aws.lambda.enhanced.out_of_memory	> 0	out_of_memory
High Iterator Age	aws.lambda.iterator_age.maximum	>= 24 hrs	high_iterator_age
High Cold Start Rate	aws.lambda.enhanced.invocations(cold_start:true)/ aws.lambda.enhanced.invocations	>= 20%	high_cold_start_rate
High Throttles	aws.lambda.throttles/aws.lambda.invocations	>= 20%	high_throttles
Increased Cost	aws.lambda.enhanced.estimated_cost	↑20%	increased_cost

To Enable and Configure a Recommended Serverless Monitor

To create a recommended monitor, you must use its respective serverless monitor ID. Note that you must also set the DATADOG_API_KEY and DATADOG_APP_KEY in your environment.

If you’d like to further configure the parameters for a recommended monitor, you can directly define the parameter values below the serverless monitor ID. Parameters not specified under a recommended monitor will use the default recommended value. The query parameter for recommended monitors cannot be directly modified and will default to using the query valued as defined above; however, you may change the threshold value in query by re-defining it within the options parameter. To delete a monitor, remove the monitor from the serverless.yml template. For further documentation on how to define monitor parameters, see the Datadog Monitors API.

Monitor creation occurs after the function is deployed. In the event that a monitor is unsuccessfully created, the function will still be successfully deployed.

To create a recommended monitor with the default values

Define the appropriate serverless monitor ID without specifying any parameter values

custom:
  datadog:
    addLayers: true
    monitors:
      - high_error_rate:

To configure a recommended monitor

custom:
  datadog:
    addLayers: true
    monitors:
      - high_error_rate:
          name: "High Error Rate with Modified Warning Threshold"
          message: "More than 10% of the function’s invocations were errors in the selected time range. Notify @[e-mail] @slack-serverless-monitors"
          tags: ["modified_error_rate", "serverless", "error_rate"]
          require_full_window: true
          priority: 2
          options:
            include_tags: true
            notify_audit: true
            thresholds:
              ok: 0.025
              warning: 0.05

To delete a monitor

Removing the serverless monitor ID and its parameters will delete the monitor.

To Enable and Configure a Custom Monitor

To define a custom monitor, you must define a unique serverless monitor ID string in addition to passing in the API key and Application key, DATADOG_API_KEY and DATADOG_APP_KEY, in your environment. The query parameter is required but every other parameter is optional. Define a unique serverless monitor ID string and specify the necessary parameters below. For further documentation on monitor parameters, see the Datadog Monitors API.

custom:
  datadog:
    addLayers: true
    monitors:
      - custom_monitor_id:
          name: "Custom Monitor"
          query: "max(next_1w):forecast(avg:system.load.1{*}, 'linear', 1, interval='60m', history='1w', model='default') >= 3"
          message: "Custom message for custom monitor. Notify @[e-mail] @slack-serverless-monitors"
          tags: ["custom_monitor", "serverless"]
          priority: 3
          options:
            enable_logs_sample: true
            require_full_window: true
            include_tags: false
            notify_audit: true
            notify_no_data: false
            thresholds:
              ok: 1
              warning: 2

Breaking Changes

v4.0.0

• The Datadog Lambda Extension is now the default mechanism for transmitting telemetry to Datadog.

Opening Issues

If you encounter a bug with this package, let us know by filing an issue! Before opening a new issue, please search the existing issues to avoid duplicates.

When opening an issue, include your Serverless Framework version, Python/Node.js version, and stack trace if available. Also, please include the steps to reproduce when appropriate.

You can also open an issue for a feature request.

Contributing

If you find an issue with this package and have a fix, open a pull request following the procedures.

Community

For product feedback and questions, join the #serverless channel in the Datadog community on Slack.

License

Unless explicitly stated otherwise, all files in this repository are licensed under the Apache License Version 2.0.

This product includes software developed at Datadog (https://www.datadoghq.com/). Copyright 2021 Datadog, Inc.